Field of the Invention
The present invention relates generally to the administration of medication, and more particularly to a closed loop system and method for adaptively controlling the administration of medication.
Related Art
Intravenous drug administration is a well-known and commonly used technique for administering medication to a patient. Intravenous administration of a medication results in a blood concentration of the medication in a patient with the object of obtaining a desired effect on that patient. An appreciation of the interrelationship between drug dose, concentration, effect and time is fundamental in pharmacology. Such an appreciation can be gained by understanding a pharmacokinetic-pharmacodynamic (PK-PD) model. This model characterizes concentration, effect and dosage by analyzing the pharmacokinetic impact of the drug dose and then the pharmacodynamic effect the drug dose has on the patient.
Specifically, pharmacokinetics (PK) seeks to describe, understand and predict the time-course of drug concentration (usually in the blood); it quantifies the relationship between dose and concentration. Pharmacodynamics (PD) seeks to describe the time-course and magnitude of the physiological effect of that concentration; it quantifies the relationship between concentration and effect. Hence, the marriage of kinetics and dynamics provides insight into the time-course of drug effect, and forms a basis for optimizing and controlling drug dosage.
One concern associated with controlling the dose/effect relationship of medication arises from the accuracy of the drug effect measurement. Another concern arises from the fact that other factors can come into play, altering the dose-effect relationship for a patient. These concerns apply to medication in general and particularly to anesthetic drugs.
Because different anesthetic drugs have different effects and side effects, drug effect can be measured in different ways. At present there are a variety of clinical indicators used as the basis for the administration of drugs to achieve a specific anesthetic state. According to conventional wisdom, the depth of anesthesia and anesthetic drug effect is clinically judged by the observation of somatic (patient movement) and autonomic (increased heart rate and blood pressure, tearing and pupil dilation) reflexes. There are, however, case reports of awareness during surgery in unparalyzed patients in whom somatic reflexes were absent. Even though these cases are relatively rare, the occurrences indicate that the observation of spontaneous movement during surgery is not foolproof.
If muscle relaxants are also present in the patient in doses that prevent movement, adequacy of anesthesia is most often assessed by the observation of autonomic reflexes, although a relationship to awareness has not been established. Another confounding factor is that anesthetic effect may be modified by disease, drugs and surgical techniques. Further, the degree of interpatient variability in the dose/effect relationship of anesthetic agents is high. In actual clinical practice, opiates and other drugs may be used in conjunction with sedative anesthetics making the clinical evaluation of anesthetic depth even more difficult.
Another conventional measure of anesthetic depth and anesthetic drug effect is the electroencephalogram (EEG). However, because changes in EEG morphology are profound and also different for each type of anesthetic being administered, interpretation of subtle changes in the raw (unprocessed) EEG requires a trained electroencephalographer and thus is typically not done during anesthesia and sedation. For this reason, computer processing of the EEG is often employed to compress the large amount of information present in the raw EEG, while preserving the information relevant to the monitoring application.
Several EEG monitors have been designed for use in the operating room, intensive care unit and other settings. These devices perform data compression and produce trends of frequency content, amplitude, and asymmetry between channels. Two main approaches have been used for this purpose: Fourier analysis and bispectral analysis.
The Fourier analysis approach represents a complex waveform as a summation of sine waves of different frequencies and amplitudes. The power spectrum can be computed from a Fast Fourier Transform (FFT) analysis. The power spectrum is in turn used to calculate a number of descriptive measures such as the spectral edge frequency (frequency below which 95% of the power spectrum (SEF 95%) or 50% of the power (median frequency or MF) exists). These measures of the EEG are often used in anesthetic pharmacological research. However, the use of power spectrum EEG analysis during clinical anesthesia has been limited for several reasons. First, different drugs have different effects on these power spectral measures. Also, at low concentrations these drugs induce activation, but at higher concentrations the drugs cause EEG slowing, even introducing iso-electric EEG episodes, referred to as burst suppression. Thus, both low and high concentrations can cause a non-monotonic relationship between the power spectral measures and the patient's clinical state.
Bispectral analysis is a quantitative EEG analysis technique that has been developed for use during anesthesia. Bispectral analysis of EEG measures consistency of phase and power relationships among the various frequencies of the EEG. The Bispectral Index® (BIS®) developed by Aspect Medical Systems, Inc., Newton, Mass., which is derived from bispectral analysis of the EEG, is a single composite EEG measure that tracks EEG changes associated with the different anesthetic states.
Principles of pharmacokinetics have recently been used to develop various schemes of computerized infusion for intravenous anesthetics and sedative drugs. A computer is provided with mean population pharmacokinetic data for the drug to be used, including the desired plasma concentration. The computer then calculates the quantity of drug and the rate of infusion for a desired (“target”) concentration; an infusion pump then delivers the required infusion rate and volume to achieve that target concentration. Such systems are referred to as Target Controlled Infusion (TCI) systems.
The problems of drug administration are not limited to anesthetic drugs, nor are they limited to intravenous delivery of medication. In clinical practice, there is no ideal plasma-concentration to produce a certain drug effect. The specific concentration required depends on factors such as individual pharmacological variability, the interaction with other simultaneously used drugs and the intensity of the surgical stimulus. In addition, since TCI is a model-based forward control only, the actual concentration realized by applying TCI techniques may vary widely due to inter-patient variability, clinical circumstances, and population characteristics.
A model-based adaptive drug delivery system and method is described by two of the inventors of the present invention in U.S. Pat. No. 6,605,072. This system estimates an individualized patient response profile using measured data points from the induction phase: the induction phase is executed in a controlled open-loop regimen, and the drug concentration versus effect for this specific patient is measured. From these measurements the patient-individualized relationship is determined and applied during closed-loop control to achieve better control. Deviations of the effect obtained from a specific administered pharmacological dose are used to shift the induction-phase response profile to match the currently observed conditions and to calculate the required change in drug administration rate.
This technique has several disadvantages:                the induction phase in a typical surgery is limited in time. In addition, it is not possible during the induction phase to step through the entire range of anesthetic agent concentrations that may occur under surgery. Instead, mathematical characteristics of the assumed relationship (e.g., symmetry around c0) are used to extrapolate the patient response profile for higher concentrations.        measurement errors during induction may jeopardize accuracy of the patient response profile—no estimate is made on how closely the real data matches the estimated response profile.        it is not possible to have the controller take over an already anesthetized patient of whom the current anesthetic state is unknown, due to the lack of induction-phase data.        it is not possible to accommodate changes in the shape of the patient's response profile during surgery, thus correcting for the effects of saturation, stimulation, etc.; the induction phase curve is shifted, but retains its shape.        
The current invention presents a method which overcomes these disadvantages.